3 UMAP
We’ll use the mathemagical Uniform Manifold Approximation and Projection (UMAP) algorithm to project the already dimension-reduced data (150 singular vectors) into 2-space. UMAP is a dimension reduction technique that builds on the notion neighbor graphs with ideas from topology. It is similar to t-SNE in its approach, but the fundamentals are based on firmer (and more complicated) mathematical theory (manifolds/topology).
# svd_ump = umap(svd$v)
# save(svd_ump, file='svd_ump.RData')
load('docs/final_data_plots/svd_ump.RData')
fig <- plot_ly(type = 'scatter', mode = 'markers')
fig <- fig %>%
add_trace(
x = svd_ump$layout[,1],
y = svd_ump$layout[,2],
text = ~paste('heading:', head ,"$<br>text: ", raw_text ),
hoverinfo = 'text',
marker = list(color='green', opacity=0.6),
showlegend = F
)
fig